ECS markers in oligodendrocyte development
This analysis was performed by MCB Lab.
Introduction
Early life stress (ELS) profoundly influences brain development by altering oligodendrogenesis and myelination, processes regulated by both glucocorticoids and the endocannabinoid system (ECS). In the referenced study, maternal separation combined with corticosterone exposure accelerated oligodendrocyte lineage progression and myelin marker expression in neonatal mice. These effects were modulated by CB1 receptor activity and 2-AG signaling, highlighting ECS–HPA axis interplay in myelin plasticity. To support these findings, we used the single-cell RNA-seq dataset from Dennis et al. (2024) [GSE237672] to better understand the expression dynamics of ECS and glucocorticoid signaling components across oligodendrocyte lineage cells during early postnatal brain development.
Dataset used can be found in Dennis et al publication.
Questions
- Which cell types during early postnatal express glucorticoid receptors and canabinoid receptors as CB1 / CB2?
- Does it have a specific OPCs / Oligodendrocytes groups expressing those markers?
Results
Cell types were annotated following mostly protocol established by Dennis et al publication.
Which cell types during early postnatal express glucorticoid receptors and canabinoid receptors as CB1 / CB2?
UMAP to overview annotated cell groups, time, area and cell phase.
Figure 1.
UMAP visualization of single-cell RNA-seq data from the V/SVZ and cortex at postnatal days P2 and P7.
Each panel shows cell clustering colored by (A) major cell type groups, (B) developmental time point, (C) brain region (area), and (D) cell cycle phase.
This overview highlights the main neural and glial populations identified in the dataset.
Does it have a specific OPCs / Oligodendrocytes groups expressing those markers?
Figure 4.
UMAP visualization of oligodendrocyte lineage subpopulations (OPCs and OLs) extracted from the combined dataset.
Cells are colored by their subcluster identity, brain region, and developmental time point.
This representation highlights the transcriptional continuum from proliferative OPCs to mature myelinating OLs, and the influence of spatial and temporal factors on lineage progression.
Figure 5.
Dot plot of differentially expressed genes within OPC and OL subclusters across cortical and V/SVZ regions.
Dot size corresponds to the proportion of cells expressing each gene, and color intensity reflects average expression level.
The results show region-specific and maturation-dependent expression patterns, emphasizing distinct molecular programs during oligodendrocyte development.
Differential Gene Expression
Table with all markers found within each Time + Area for subpopulations of OPCs + OLs.
| Column | Description |
|---|---|
| Gene | The gene symbol or ID of the marker gene identified as differentially expressed. Each entry corresponds to one gene tested across clusters or groups. |
| Cluster | The cell cluster (or subpopulation) in which the gene is more highly expressed compared to others. For example, a specific OPC or OL subtype. |
| Area | The anatomical region (e.g., cortex, corpus callosum, spinal cord) where this cluster’s cells were sampled. Helps distinguish spatial differences in gene expression. |
| Age | The time point or developmental stage (e.g., P7, Adult) at which cells were collected. Allows temporal comparisons of expression changes. |
| avg_log2FC | The average log₂ fold-change in expression between cells in the cluster of interest and all other cells. Positive values indicate upregulation in this cluster; negative values indicate downregulation. |
| pct.1 | The percentage of cells in the target cluster where this gene is detected (nonzero expression). Higher values = more consistently expressed within the cluster. |
| pct.2 | The percentage of cells in all other clusters (combined) expressing the same gene. Used to assess specificity of expression. |
| p_val_adj | The adjusted p-value (after multiple testing correction, e.g., Bonferroni or FDR) indicating the statistical significance of the differential expression. Smaller values = stronger evidence that the gene is a true marker. |
Table 1.
List of marker genes identified for each OPC/OL subpopulation across different areas and developmental time points.
The table includes fold-change values, detection percentages, and adjusted p-values for statistical significance.